Merge pull request #2 from cosbidev/v2.0.3

V2.0.3

Author: matteotortora

docs/source/API/analytics.rst

@@ -1,8 +1,22 @@
 Analytics
 ========
 
+visualization
+-------------
 .. automodule:: pytrack.analytics.visualization
    :members:
    :undoc-members:
    :show-inheritance:
    :inherited-members:
+
+video
+-------------
+.. automodule:: pytrack.analytics.video
+   :members:
+   :undoc-members:
+
+plugins
+-------------
+.. automodule:: pytrack.analytics.plugins
+   :members:
+   :undoc-members:

docs/source/API/graph.rst

@@ -27,4 +27,4 @@ utils
 .. automodule:: pytrack.graph.utils
    :members:
    :undoc-members:
-   :show-inheritance:
+   :show-inheritance:

docs/source/API/matching.rst

@@ -7,6 +7,12 @@ candidate
    :members:
    :undoc-members:
 
+cleaning
+-------------
+.. automodule:: pytrack.matching.cleaning
+   :members:
+   :undoc-members:
+
 matcher
 -------------
 .. automodule:: pytrack.matching.matcher

docs/source/conf.py

@@ -24,7 +24,7 @@
 author = 'Matteo Tortora'
 
 # The full version, including alpha/beta/rc tags
-release = '1.0.3'
+release = '2.0.3'
 
 # -- General configuration ---------------------------------------------------
 

pytrack/analytics/plugins.py

@@ -0,0 +1,16 @@
+class Segmenter:
+    """ Skeleton parent class to perform the segmentation operation.
+
+    """
+    def __init__(self):
+        pass
+
+    def processing(self, img):
+        """ It takes an input image and returns the processed image.
+        """
+        pass
+
+    def run(self, img):
+        """ It takes an input image and returns the mask of the segmented image.
+        """
+        pass

pytrack/analytics/segmentator.py

@@ -5,6 +5,8 @@
 import cv2
 import requests
 
+from pytrack.analytics import plugins
+
 PREV_PAN_ID = None
 
 
@@ -102,7 +104,7 @@ def extract_streetview_pic(point, api_key, size="640x640", heading=90, pitch=-10
     return pic, meta
 
 
-def save_streetview(pic, meta, folder_path):
+def save_streetview(pic, meta, folder_path, model=None):
     """ Save streetview pic and metadata in the desired path.
 
     Parameters
@@ -121,5 +123,9 @@ def save_streetview(pic, meta, folder_path):
     with open(os.path.join(folder_path, 'pic.png'), 'wb') as file:
         file.write(pic)
 
+    if isinstance(model, plugins.Segmenter):
+        with open(os.path.join(folder_path, 'pic_seg.png'), 'wb') as file:
+            file.write(model.run(pic))
+
     with open(os.path.join(folder_path, 'metadata.json'), 'w+') as out_file:
         json.dump(meta, out_file)

pytrack/analytics/video.py

@@ -51,7 +51,7 @@ def haversine_dist(lat1, lon1, lat2, lon2, earth_radius=EARTH_RADIUS_M):
         Earth's radius
     Returns
     ----------
-    dists: float
+    dist: float
         Distance in units of earth_radius
     """
     # convert decimal degrees to radians 

pytrack/graph/distance.py

@@ -0,0 +1,77 @@
+from pytrack.graph import distance
+
+
+def veldist_filter(traj, th_dist=5, th_vel=3):
+    """ It filters the GPS trajectory combining speed and distance between adjacent points.
+    If the adjacent point distance does not exceed the threshold and the speed is less than th_vel (m/s), the current
+    trajectory point is ignored.
+
+    Parameters
+    ----------
+    traj: pandas.DataFrame
+        Dataframe containing 3 columns [timestamp, latitude, longitude].
+    th_dist: float, optional, default: 5 meters.
+        Threshold for the distance of adjacent points.
+    th_vel: float, optional, default: 3 m/s.
+        Threshold for the velocity.
+
+    Returns
+    -------
+    df: pandas.DataFrame
+        Filtered version of the input dataframe.
+    """
+
+    df = traj.copy()
+
+    i = 0
+    while True:
+        if i == df.shape[0]-1:
+            break
+        deltat = (df["datetime"][i+1]-df["datetime"][i]).total_seconds()
+        dist = distance.haversine_dist(*tuple(df.iloc[i, [1, 2]]), *tuple(df.iloc[i+1, [1, 2]]))
+
+        if dist < th_dist and dist/deltat < th_vel:
+            df.drop([i+1], inplace=True)
+            df.reset_index(drop=True, inplace=True)
+        else:
+            i += 1
+
+    return df
+
+
+def park_filter(traj, th_dist=50, th_time=30):
+    """ It removes parking behaviour by eliminating those points that remain in a certain area
+    for a given amount of time.
+
+    Parameters
+    ----------
+    traj: pandas.DataFrame
+        Dataframe containing 3 columns [timestamp, latitude, longitude].
+    th_dist: float, optional, default: 50 meters.
+        Threshold for the distance of adjacent points.
+    th_time: float, optional, default: 30 min.
+        Threshold for the delta time.
+
+    Returns
+    -------
+    df: pandas.DataFrame
+        Filtered version of the input dataframe.
+    """
+
+    df = traj.copy()
+
+    i = 0
+    while True:
+        if i == df.shape[0]-1:
+            break
+        deltat = (df["datetime"][i+1]-df["datetime"][i]).total_seconds()
+        deltad = distance.haversine_dist(*tuple(df.iloc[i, [1, 2]]), *tuple(df.iloc[i+1, [1, 2]]))
+
+        if deltad < th_dist and deltat > th_time:
+            df.drop([i+1], inplace=True)
+            df.reset_index(drop=True, inplace=True)
+        else:
+            i += 1
+
+    return df
+

pytrack/matching/cleaning.py

@@ -1,11 +1,8 @@
-from . import mpmatching
-
 class Matcher:
-    def __init__(self, G, trellis):
-        self.G
-        self.trellis
-
-    def match(self):
-        path_prob, predecessor = mpmatching.viterbi_search(self.G_interp, self.trellis, "start", "target")
+    """ Skeleton parent class to perform the matching operation.
+    """
+    def __init__(self, G):
+        self.G = G
 
-        return results
+    def match(self, points):
+        pass